The field of inter-organizational relations : a jungle or an Italian garden?

Each chapter in this Handbook contains an explicit assessment of priorities for future research that would extend and deepen an understanding of IOR. Given the diversity of contributions to this volume, it is perhaps not surprising that recommendations for future research are varied. And because the three sets of contributions start from different points-empirical manifestations, theoretical and disciplinary perspectives, and thematic interests-so the recommendations, too, might be expected to lead along different paths, 'cutting' and framing future research topics in different ways. Nevertheless, as others have suggested (Brass et al. 2005) it is possible to see some points of convergence across all three parts of the Handbook. We begin our discussion of the contributions and suggestions for the future by focusing on these points of convergence. We then look in turn at the specific ideas that emerge from, and relate to, the specific framings of each of the parts. Finally, we draw together insights about methodological issues

The Effects of Testosterone on Leydig Cell Development in Male YHR+ Mice

Leydig cells (LC) are specialized cells in the testis that develop during puberty and are responsible for producing testosterone. Luteinizing Hormone (LH) and testosterone are important for LC development. Binding of LH to its receptor (LHR) initiates the production of testosterone. Constitutively active mutations in LHR have been identified in humans resulting in puberty in males as young as 3 or 4 years of age. A transgenic mouse (YHR+), was generated which mimics the constitutively active LHR by fusing the hormone, human chorionic gonadotropin, to LHR to continually activate the receptor. Testosterone levels in YHR+ mice are high at neonatal ages. Previous studies in the lab have shown that YHR+ mice have decreased LC numbers compared to wild type (WT) mice. It was hypothesized that high levels of testosterone at neonatal ages was responsible for the decrease in LC numbers and was causing a decrease in the proliferation of LCs. To test this hypothesis, the action of testosterone was blocked with the androgen antagonist, flutamide, and the total number of LCs as well as the number of proliferating LCs were determined. There was no significant increase in LC number or in proliferation of flutamide treated YHR+ mice suggesting that other factors may be involved in the decrease in LC number. Together, these results suggest that high neonatal testosterone is not sufficient to inhibit LC development

Reducing the Probability of False Positive Research Findings by Pre-Publication Validation - Experience with a Large Multiple Sclerosis Database

*Objective*
We have assessed the utility of a pre-publication validation policy in reducing the probability of publishing false positive research findings. 
*Study design and setting*
The large database of the Sylvia Lawry Centre for Multiple Sclerosis Research was split in two parts: one for hypothesis generation and a validation part for confirmation of selected results. We present case studies from 5 finalized projects that have used the validation policy and results from a simulation study.
*Results*
In one project, the "relapse and disability" project as described in section II (example 3), findings could not be confirmed in the validation part of the database. The simulation study showed that the percentage of false positive findings can exceed 20% depending on variable selection. 
*Conclusion*
We conclude that the validation policy has prevented the publication of at least one research finding that could not be validated in an independent data set (and probably would have been a "true" false-positive finding) over the past three years, and has led to improved data analysis, statistical programming, and selection of hypotheses. The advantages outweigh the lost statistical power inherent in the process

Multiple sclerosis, the measurement of disability and access to clinical trial data

Background: Inferences about long-term effects of therapies in multiple sclerosis (MS) have been based on surrogate markers studied in short-term trials. Nevertheless, MS trials have been getting steadily shorter despite the lack of a consensus definition for the most important clinical outcome - unremitting progression of disability. Methods: We have examined widely used surrogate markers of disability progression in MS within a unique database of individual patient data from the placebo arms of 31 randomised clinical trials. Findings: Definitions of treatment failure used in secondary progressive MS trials include much change unrelated to the target of unremitting disability. In relapsing-remitting MS, disability progression by treatment failure definitions was no more likely than similarly defined improvement for these disability surrogates. Existing definitions of disease progression in relapsing-remitting trials encompass random variation, measurement error and remitting relapses and appear not to measure unremitting disability. Interpretation: Clinical surrogates of unremitting disability used in relapsing -remitting trials cannot be validated. Trials have been too short and/or degrees of disability change too small to evaluate unremitting disability outcomes. Important implications for trial design and reinterpretation of existing trial results have emerged long after regulatory approval and widespread use of therapies in MS, highlighting the necessity of having primary trial data in the public domain

Treating systematic errors in multiple sclerosis data

Multiple sclerosis (MS) is characterized by high variability between patients and, more importantly here, within an individual over time. This makes categorization and prognosis difficult. Moreover, it is unclear to what degree this intra-individual variation reflects the long-term course of irreversible disability and what is attributable to short-term processes such as relapses, to interrater variability and to measurement error. Any investigation and prediction of the medium or long term evolution of irreversible disability in individual patients is therefore confronted with the problem of systematic error in addition to random fluctuations. The approach described in this article aims to assist in detecting relapses in disease curves and in identifying the underlying disease course. To this end neurological knowledge was transformed into simple rules which were then implemented into computer algorithms for pre-editing disease curves. Based on simulations it is shown that pre-editing time series of disability measured with the Expanded Disability Status Scale (EDSS) can lead to more robust and less biased estimates for important disease characteristics, such as baseline EDSS and time to reach certain EDSS levels or sustained progression

Treating Systematic Errors in Multiple Sclerosis Data

Multiple sclerosis (MS) is characterized by high variability between patients and, more importantly here, within an individual over time. This makes categorization and prognosis difficult. Moreover, it is unclear to what degree this intra-individual variation reflects the long-term course of irreversible disability and what is attributable to short-term processes such as relapses, to interrater variability and to measurement error. Any investigation and prediction of the medium or long term evolution of irreversible disability in individual patients is therefore confronted with the problem of systematic error in addition to random fluctuations. The approach described in this article aims to assist in detecting relapses in disease curves and in identifying the underlying disease course. To this end neurological knowledge was transformed into simple rules which were then implemented into computer algorithms for pre-editing disease curves. Based on simulations it is shown that pre-editing time series of disability measured with the Expanded Disability Status Scale (EDSS) can lead to more robust and less biased estimates for important disease characteristics, such as baseline EDSS and time to reach certain EDSS levels or sustained progression

Genetic, environmental and stochastic factors in monozygotic twin discordance with a focus on epigenetic differences

Genetic-epidemiological studies on monozygotic (MZ) twins have been used for decades to tease out the relative contributions of genes and the environment to a trait. Phenotypic discordance in MZ twins has traditionally been ascribed to non-shared environmental factors acting after birth, however recent data indicate that this explanation is far too simple. In this paper, we review other reasons for discordance, including differences in the in utero environment, genetic mosaicism, and stochastic factors, focusing particularly on epigenetic discordance. Epigenetic differences are gaining increasing recognition. Although it is clear that in specific cases epigenetic alterations provide a causal factor in disease etiology, the overall significance of epigenetics in twin discordance remains unclear. It is also challenging to determine the causality and relative contributions of environmental, genetic, and stochastic factors to epigenetic variability. Epigenomic profiling studies have recently shed more light on the dynamics of temporal methylation change and methylome heritability, yet have not given a definite answer regarding their relevance to disease, because of limitations in establishing causality. Here, we explore the subject of epigenetics as another component in human phenotypic variability and its links to disease focusing particularly on evidence from MZ twin studies

Evaluating digital policy interventions: studies in violence prevention, deradicalization, and investor protection

Social media platforms allow individuals without great technical knowledge or financial capital to spread violent content and radical messages among a large audience, bypassing traditional media. As violence and radical actions cause significant economic damage and undermine democratic institutions, security agencies have responded by using the same platforms to target at-risk individuals with their prevention programs. The literature has shown that such online programs can be effective in reducing victimization and perpetration rates. However, despite the large number of programs implemented, there is a significant lack of rigorous impact evaluations. This thesis contributes to the literature by developing a conceptual framework for evaluating the impact and economic efficiency of online programs for crime prevention in general. Furthermore, it contributes by evaluating the impact of two online programs in the areas of violence prevention and deradicalization. To reassess the impact of such online programs in a different prevention context, the thesis also evaluates a measure for investor protection in the context of the Bitcoin cryptocurrency

Liability For Artificial Intelligence And EU Consumer Law

The new Directives on Digital Contracts – the Digital Content and Services Directive (DCSD) 2019/770 and the Sale of Goods Directive (SGD) 2019/771 – are often seen as important steps in adapting European private law to the requirements of the digital economy. However, neither directive contains special rules for new technologies such as Artificial Intelligence (AI). In light of this issue, the following paper discusses whether existing EU consumer law is equipped to deal with situations in which AI systems are either used for internal purposes by companies or offered to consumers as the main subject matter of the contract. This analysis will reveal a number of gaps in current EU consumer law and briefly discuss upcoming legislation